会议专题

A Hierarchical Fuzzy-neural Multi-model Applied in Nonlinear Systems Identification and Control

  The paper brings forward a hierarchical fuzzy-neural multi-model with recurrent neural procedural consequent par for systems identification,states estimation and adaptive control of complex nonlinear plants.The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive trajectory tracking control systems design.The designed local control laws are coordinated by a fuzzy rule-based control system.The upper level defuzzyfication is performed by a recurrent neural network.The applicability of the proposed intelligent control system is confirmed by simulation examples and by a DC-motor identification and control experimental results.Two main cases of a reference and plant output fuzzyfication are considered—a two membership functions without overlapping and a three membership functions with overlapping.In both cases a good convergent results are obtained.

Fuzzy-neural hierarchical multi-model Recurrent neural networks Systems identification

Feng Ye Wei-min Qi

School of Physics & Information Engineering Jianghan University Wuhan, China

国际会议

2013 2nd International Symposium on Computer,Communication,Control and Automation(ISCCCA-13)(2013年第二届计算机、通信与自动化国际会议)

太原

英文

183-187

2013-04-06(万方平台首次上网日期,不代表论文的发表时间)